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dc.contributor.authorPei, Shichao
dc.contributor.authorYu, Lu
dc.contributor.authorZhang, Xiangliang
dc.date.accessioned2021-06-09T05:14:07Z
dc.date.available2021-06-09T05:14:07Z
dc.date.issued2021
dc.identifier.citationPei, S., Yu, L., & Zhang, X. (2021). Set-aware Entity Synonym Discovery with Flexible Receptive Fields. IEEE Transactions on Knowledge and Data Engineering, 1–1. doi:10.1109/tkde.2021.3087532
dc.identifier.issn2326-3865
dc.identifier.doi10.1109/TKDE.2021.3087532
dc.identifier.urihttp://hdl.handle.net/10754/669461
dc.description.abstractEntity synonym discovery (ESD) from text corpus is an essential problem in many entity-leveraging applications, e.g., web search and question answering. This paper aims to address three limitations that widely exist in the current ESD solutions: 1) the lack of effective utilization for synonym set information; 2) the feature extraction of entities from restricted receptive fields; and 3) the incapacity to capture higher-order contextual information. We propose a novel set-aware ESD model that enables a flexible receptive field for ESD by making a breakthrough in using entity synonym set information. The contextual information of entities and entity synonym sets are arranged by a two-level network from which entities and entity synonym sets can be mapped into the same embedding space to facilitate ESD by encoding the high-order contexts from flexible receptive fields. Extensive experimental results on public datasets show that our model consistently outperforms the state-of-the-art with significant improvement.
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9448379/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9448379/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9448379
dc.rightsArchived with thanks to IEEE Transactions on Knowledge and Data Engineering
dc.subjectEntity Synonym Discovery
dc.subjectEntity Synonym Set
dc.subjectGraph Neural Network
dc.subjectFlexible Receptive Field
dc.titleSet-aware Entity Synonym Discovery with Flexible Receptive Fields
dc.typeArticle
dc.contributor.departmentComputer Science
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.contributor.departmentMachine Intelligence & kNowledge Engineering Lab
dc.identifier.journalIEEE Transactions on Knowledge and Data Engineering
dc.eprint.versionPost-print
kaust.personPei, Shichao
kaust.personYu, Lu
kaust.personZhang, Xiangliang
refterms.dateFOA2021-06-10T05:27:45Z


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